Welcome

Welcome to EPsy 3264: Basic and Applied Statistics.


Instructor

Andrew Zieffler (zief0002@umn.edu)
Office: Education Sciences Building 178
Office Hours: Tuesday 9:00 AM–10:00 AM; and by appointment


Classroom


Course Content and Syllabus

EPsy 3264 is designed to engage students using a modeling and simulation approach to inference. This course uses pedagogical principles that are founded in research, such as daily small group activities and discussion. Upon completion of this course, students should have an understanding of the foundational concepts of data, variation and inference, as well as an appreciation for the fundamental role that statistics plays in a host of disciplines, such as business, economics, law, and medicine.

  • The course syllabus is available here.


Course Materials


TinkerPlots on Campus

TinkerPlots is installed on four computers in the Walter Library computer lab (WALIB 105; Computers 18–21). These computers are marked with a sign indicating that TinkerPlots is installed on them.


Getting Help

There are several things you can do to be successful in this course. First and foremost, complete all of the readings and come prepared to class. Complete all of the lab assignments. Ask questions. If you are experiencing problems, need help, or have any questions or other course-related concerns, do not hesitate to get in touch with the instructor or one of the Teaching Assisstants. Note: If you are unable to meet during the scheduled office hours, we can work with you to find a day/time that works in your schedule!


We have four Teaching Assisstants who you can help you with the course material:


Jesslyn Valerie (valer066@umn.edu)
Office: Education Sciences Building 196
Office Hours: Wednesday 1:00 PM–2:00 PM; and by appointment


Sam Ihlenfeldt (ihlen010@umn.edu)
Office: Education Sciences Building 193
Office Hours: Wednesday 11:30 AM PM–12:30 PM; and by appointment


Johanna Schultz (schu4338@umn.edu)
Office: Education Sciences Building 192
Office Hours: Monday 10:00 AM–11:00 AM; and by appointment


Manos Hatzimalonas (chatz006@umn.edu)
Office: Education Sciences Building 192
Office Hours: Thursday 1:30 PM–3:30 PM; and by appointment


Before coming for help, you may want to review the Asking Helpful Questions section of the website.

Schedule

Below is the tenative schedule for the class. The dates are subject to change at the instructor’s discretion. Readings should be completed prior to class. Assignments are due at the beginning of the class period that they are due


Calendar


Unit 0: Introduction
  Sept. 04 Introduction to EPsy 3264
Unit 1: Modeling and Simulation
  Sept. 09 Reading: Introduction
Reading: Modeling & Simulation
Spotify Playlists
  Sept. 11 Reading: Generating Data From Models
Generating Random Data—Cat Factory
  Sept. 16 Reading: Monte Carlo Simulation
Assignment #1 Due (Learning TinkerPlots)
Introduction to Monte Carlo Simulation
  Sept. 18 Automating the Simulation Process
  Sept. 23 Assignment #2 Due (Free Throws)
Group Quiz #1
Unit 2: Modeling Sampling Variation
  Sept. 25 Reading: Modeling Sampling Variation
Monday Breakups
  Sept. 30 Features of Distributions
  Oct. 02 Reading: Describing Distributions
Assignment #3 Due (Distracted Driving)
Helper or Hinderer
  Oct. 07 Comparing Hand Spans
  Oct. 09 Assignment #4 Due (College Debt)
Racial Disparities in Police Stops
  Oct. 14 Group Quiz #2
Unit 3: Experimental Variation and the Randomization Test
  Oct. 16 Reading: Experimental Variation and the Randomization Test
Memorization
  Oct. 21 Memorization using TinkerPlots
  Oct. 23 Sleep Deprivation
  Oct. 28 Reading: Quantifying Results: p-Value
Contagious Yawns
  Oct. 30 Reading: Internal Validity Evidence and Random Assignment
Assignment #5 Due (Dolphin Therapy)
Strength Shoe
  Nov. 04 Group Quiz #3
Unit 4: Sampling Variation and the Bootstrap Test
  Nov. 06 Reading: Sampling Variation and the Bootstrap Test
Speed Skating
  Nov. 11 Reading: External Validity Evidence and Random Sampling
Gettysburg Address
  Nov. 13 Reading: Validity Evidence and Inferences
Reading: Observational Studies and the Bootstrap Test
Murderous Nurse
  Nov. 18 Assignment #6 Due (Lyric Readability)
Movie Sequels
  Nov. 20 Group Quiz #4
Unit 5: Estimating Uncertainty
  Nov. 25 Reading: Estimating Uncertainty
Kissing the ‘Right’ Way
  Nov. 27 No Class: Take a well-earned break
  Dec. 02 Cuddling Preferences
  Dec. 04 Reading: Uncertainty and Bias
Assignment #7 Due (College Student Health Survey)
Minnesota College Debt
  Dec. 09 Comparing Cuddling Preferences
  Dec. 11 Group Quiz #5
  Dec. 12 Assignment #8 Due (Dolphins and Pigs)
Due by 12:00pm in EdSciB 250

Assignments

Below are the due dates for the assignments, as well as links to the PDF files for each assignment. The due dates may change at the instructor’s discretion. Any revised due dates will be announced in class and posted to the website.


Assignment Due Date PDF
Assignment #1: Learning TinkerPlots Sept. 16
Assignment #2: Free Throws Sept. 23
Assignment #3: Distracted Driving Oct. 2
Assignment #4: College Debt Oct. 9
Assignment #5: Dolphin Therapy Oct.30
Assignment #6: Lyric Readability Nov. 18
Assignment #7: College Student Health Survey Dec. 2
Assignment #8: Dolphins and Pigs Dec. 11

Asking Helpful Questions

Asking questions is part of the learning process, and if you are stuck on a homework assignment or concerned about your course performance, please ask! However, since your work on the assignments is one way we evaluate your performance, there is a delicate balance to how the instructors and TAs will respond to your questions.

Below are a few examples of the types of questions or statements that students have had for the teaching team that are difficult for the teaching team to address.


Requests for “Pre-Grading”

Here are examples of these types of requests:

  • “Could you look over my assignment and let me know if I did anything wrong?”
  • “Is my answer correct?”
  • “Did I write enough for this answer?”

The teaching team will not directly answer these requests. You will be redirected to ask something more specific.

What to Do Instead

  • If you completed the assignment without any trouble, then be confident in your work and simply submit the assignment! 😄
  • If you’re unsure about something specific, then ask about that specific thing!
    • Helpful example: “Do we need to include the plot for Question 2?”
    • Helpful example: “Do we need to define the p-value when using it as evidence for answering the research question?”
  • If you are having trouble knowing what to include in your answer, then ask about what the question is looking for
    • Helpful example: “Question 4 asks us to refer to our Sampler in the answer. How much detail is needed when referring to the Sampler?”
    • Helpful example: “I know Question 8 is asking about […], but I’m not sure what this question is looking for. Is there another way to restate this question?”


Completely Open-Ended Requests

Here are examples of these types of requests:

  • “I looked at the homework, but I do not know what to do. Can you give me a hint?”
  • “I did Step 1, what do I do next?”

The teaching team finds these requests difficult because the assignments are an evaluation of your skills and knowledge. So when you ask these types of questions it begins to blur the lines about whether the answers on the homework reflect what you know (we can’t do the homework for you).

What to Do Instead

  • Identify something specific to ask about. What specifically are you unsure about? Putting in additional thought to ask a more specific question may both (1) help you better understand the assignment, and (2) actually hep you answer your own question!
    • Since the homework typically reflects what you did during the in-class activities, the most helpful thing to do is to ask which part of an activity you should review. This is partly why understanding the in-class activities is crucial.
    • Helpful example: “I’m concerned my TinkerPlots sampler is not set up correctly. Which activity provides a similar example that I can use as a comparison?”


Other Requests that are Difficult to Respond To

Here are examples of these types of requests:

  • “I really need an ‘A’ in this class.”
  • “I’m so close to a higher grade. Can you look over my past assignments and find a way to give me some points back?”

We understand that your grade is important to you. However, even if it is not intended, the implication of these statements is for the teaching team to do something unethical, such as grade things differently for different students.

What to Do Instead

  • Ask about ways to improve your future performance in the course
    • Helpful example: “I really want to do well in this class. What else can I do to ensure I succeed?”
    • Helpful example: “I would like to earn a better grade on future assignments and quizzes. What advice do you have?”
  • Ask about predicting what your potential grade may be, based on a number of scenarios – we’re happy to forecast your grade for you!
    • Helpful example: “Score-wise, what do I need on the remaining coursework to earn an ‘A’ in the course?”
  • If you think your grade or scores were computed incorrectly, then please ask; we will double-check!


Final Suggestions for Effective Professional Habits

  • Please ask for assistance before a deadline! Asking a lot of homework questions 10 minutes before a deadline or after a deadline reinforces unhelpful work habits and may put you and the teaching team in a difficult situation. It also conveys, whether you meant to or not, that you do not care about the learning; only the grade.
  • For any appointments outside of office hours, please show up! If you cannot make the agreed upon meeting, please send a message of cancellation to the instructor or TA you had planned to meet with. Not showing up to a scheduled appointment without communicating is a bad habit to form and is unprofessional in any setting. A little bit of professionalism goes a long way!